Dataset statistics
| Number of variables | 12 |
|---|---|
| Number of observations | 891 |
| Missing cells | 14 |
| Missing cells (%) | 0.1% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 77.7 KiB |
| Average record size in memory | 89.3 B |
Variable types
| Numeric | 5 |
|---|---|
| Categorical | 7 |
Name has a high cardinality: 891 distinct values | High cardinality |
Ticket has a high cardinality: 681 distinct values | High cardinality |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Survived is highly correlated with Sex | High correlation |
Sex is highly correlated with Survived | High correlation |
Survived is highly correlated with Sex | High correlation |
Pclass is highly correlated with Fare and 1 other fields | High correlation |
Sex is highly correlated with Survived | High correlation |
Age is highly correlated with Age_cut | High correlation |
SibSp is highly correlated with Parch | High correlation |
Parch is highly correlated with SibSp | High correlation |
Fare is highly correlated with Pclass | High correlation |
Embarked is highly correlated with Pclass | High correlation |
Age_cut is highly correlated with Age | High correlation |
Age_cut has 14 (1.6%) missing values | Missing |
PassengerId is uniformly distributed | Uniform |
Name is uniformly distributed | Uniform |
Ticket is uniformly distributed | Uniform |
PassengerId has unique values | Unique |
Name has unique values | Unique |
SibSp has 608 (68.2%) zeros | Zeros |
Parch has 678 (76.1%) zeros | Zeros |
Fare has 15 (1.7%) zeros | Zeros |
Reproduction
| Analysis started | 2022-04-23 13:51:40.247477 |
|---|---|
| Analysis finished | 2022-04-23 13:51:55.644123 |
| Duration | 15.4 seconds |
| Software version | pandas-profiling v3.1.0 |
| Download configuration | config.json |
| Distinct | 891 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 446 |
| Minimum | 1 |
|---|---|
| Maximum | 891 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.1 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 45.5 |
| Q1 | 223.5 |
| median | 446 |
| Q3 | 668.5 |
| 95-th percentile | 846.5 |
| Maximum | 891 |
| Range | 890 |
| Interquartile range (IQR) | 445 |
Descriptive statistics
| Standard deviation | 257.353842 |
|---|---|
| Coefficient of variation (CV) | 0.5770265516 |
| Kurtosis | -1.2 |
| Mean | 446 |
| Median Absolute Deviation (MAD) | 223 |
| Skewness | 0 |
| Sum | 397386 |
| Variance | 66231 |
| Monotonicity | Strictly increasing |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 1 | 1 | 0.1% |
| 599 | 1 | 0.1% |
| 588 | 1 | 0.1% |
| 589 | 1 | 0.1% |
| 590 | 1 | 0.1% |
| 591 | 1 | 0.1% |
| 592 | 1 | 0.1% |
| 593 | 1 | 0.1% |
| 594 | 1 | 0.1% |
| 595 | 1 | 0.1% |
| Other values (881) | 881 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 |
| Value | Count | Frequency (%) |
| 891 | 1 | |
| 890 | 1 | |
| 889 | 1 | |
| 888 | 1 | |
| 887 | 1 | |
| 886 | 1 | |
| 885 | 1 | |
| 884 | 1 | |
| 883 | 1 | |
| 882 | 1 |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| 0 | |
|---|---|
| 1 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 1 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 342 |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 342 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| 3 | |
|---|---|
| 1 | |
| 2 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 3 |
|---|---|
| 2nd row | 1 |
| 3rd row | 3 |
| 4th row | 1 |
| 5th row | 3 |
Common Values
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 216 | |
| 2 | 184 | 20.7% |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 216 | |
| 2 | 184 | 20.7% |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 891 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| Braund, Mr. Owen Harris | 1 |
|---|---|
| Boulos, Mr. Hanna | 1 |
| Frolicher-Stehli, Mr. Maxmillian | 1 |
| Gilinski, Mr. Eliezer | 1 |
| Murdlin, Mr. Joseph | 1 |
| Other values (886) |
Length
| Max length | 82 |
|---|---|
| Median length | 25 |
| Mean length | 26.96520763 |
| Min length | 12 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 891 ? |
|---|---|
| Unique (%) | 100.0% |
Sample
| 1st row | Braund, Mr. Owen Harris |
|---|---|
| 2nd row | Cumings, Mrs. John Bradley (Florence Briggs Thayer) |
| 3rd row | Heikkinen, Miss. Laina |
| 4th row | Futrelle, Mrs. Jacques Heath (Lily May Peel) |
| 5th row | Allen, Mr. William Henry |
Common Values
| Value | Count | Frequency (%) |
| Braund, Mr. Owen Harris | 1 | 0.1% |
| Boulos, Mr. Hanna | 1 | 0.1% |
| Frolicher-Stehli, Mr. Maxmillian | 1 | 0.1% |
| Gilinski, Mr. Eliezer | 1 | 0.1% |
| Murdlin, Mr. Joseph | 1 | 0.1% |
| Rintamaki, Mr. Matti | 1 | 0.1% |
| Stephenson, Mrs. Walter Bertram (Martha Eustis) | 1 | 0.1% |
| Elsbury, Mr. William James | 1 | 0.1% |
| Bourke, Miss. Mary | 1 | 0.1% |
| Chapman, Mr. John Henry | 1 | 0.1% |
| Other values (881) | 881 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| mr | 521 | 14.4% |
| miss | 182 | 5.0% |
| mrs | 129 | 3.6% |
| william | 64 | 1.8% |
| john | 44 | 1.2% |
| master | 40 | 1.1% |
| henry | 35 | 1.0% |
| george | 24 | 0.7% |
| james | 24 | 0.7% |
| charles | 23 | 0.6% |
| Other values (1515) | 2538 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| male | |
|---|---|
| female |
Length
| Max length | 6 |
|---|---|
| Median length | 4 |
| Mean length | 4.704826038 |
| Min length | 4 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | male |
|---|---|
| 2nd row | female |
| 3rd row | female |
| 4th row | female |
| 5th row | male |
Common Values
| Value | Count | Frequency (%) |
| male | 577 | |
| female | 314 |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| male | 577 | |
| female | 314 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 89 |
|---|---|
| Distinct (%) | 10.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 29.69911765 |
| Minimum | 0.42 |
|---|---|
| Maximum | 80 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.1 KiB |
Quantile statistics
| Minimum | 0.42 |
|---|---|
| 5-th percentile | 6 |
| Q1 | 22 |
| median | 29.69911765 |
| Q3 | 35 |
| 95-th percentile | 54 |
| Maximum | 80 |
| Range | 79.58 |
| Interquartile range (IQR) | 13 |
Descriptive statistics
| Standard deviation | 13.00201523 |
|---|---|
| Coefficient of variation (CV) | 0.4377912967 |
| Kurtosis | 0.9662793027 |
| Mean | 29.69911765 |
| Median Absolute Deviation (MAD) | 6.300882353 |
| Skewness | 0.434488094 |
| Sum | 26461.91382 |
| Variance | 169.0523999 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 29.69911765 | 177 | 19.9% |
| 24 | 30 | 3.4% |
| 22 | 27 | 3.0% |
| 18 | 26 | 2.9% |
| 28 | 25 | 2.8% |
| 30 | 25 | 2.8% |
| 19 | 25 | 2.8% |
| 21 | 24 | 2.7% |
| 25 | 23 | 2.6% |
| 36 | 22 | 2.5% |
| Other values (79) | 487 |
| Value | Count | Frequency (%) |
| 0.42 | 1 | 0.1% |
| 0.67 | 1 | 0.1% |
| 0.75 | 2 | 0.2% |
| 0.83 | 2 | 0.2% |
| 0.92 | 1 | 0.1% |
| 1 | 7 | |
| 2 | 10 | |
| 3 | 6 | |
| 4 | 10 | |
| 5 | 4 | 0.4% |
| Value | Count | Frequency (%) |
| 80 | 1 | 0.1% |
| 74 | 1 | 0.1% |
| 71 | 2 | |
| 70.5 | 1 | 0.1% |
| 70 | 2 | |
| 66 | 1 | 0.1% |
| 65 | 3 | |
| 64 | 2 | |
| 63 | 2 | |
| 62 | 4 |
| Distinct | 7 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.5230078563 |
| Minimum | 0 |
|---|---|
| Maximum | 8 |
| Zeros | 608 |
| Zeros (%) | 68.2% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.1 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 1 |
| 95-th percentile | 3 |
| Maximum | 8 |
| Range | 8 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 1.102743432 |
|---|---|
| Coefficient of variation (CV) | 2.108464374 |
| Kurtosis | 17.88041973 |
| Mean | 0.5230078563 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 3.695351727 |
| Sum | 466 |
| Variance | 1.216043077 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 608 | |
| 1 | 209 | 23.5% |
| 2 | 28 | 3.1% |
| 4 | 18 | 2.0% |
| 3 | 16 | 1.8% |
| 8 | 7 | 0.8% |
| 5 | 5 | 0.6% |
| Value | Count | Frequency (%) |
| 0 | 608 | |
| 1 | 209 | 23.5% |
| 2 | 28 | 3.1% |
| 3 | 16 | 1.8% |
| 4 | 18 | 2.0% |
| 5 | 5 | 0.6% |
| 8 | 7 | 0.8% |
| Value | Count | Frequency (%) |
| 8 | 7 | 0.8% |
| 5 | 5 | 0.6% |
| 4 | 18 | 2.0% |
| 3 | 16 | 1.8% |
| 2 | 28 | 3.1% |
| 1 | 209 | 23.5% |
| 0 | 608 |
| Distinct | 7 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.3815937149 |
| Minimum | 0 |
|---|---|
| Maximum | 6 |
| Zeros | 678 |
| Zeros (%) | 76.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.1 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 2 |
| Maximum | 6 |
| Range | 6 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 0.8060572211 |
|---|---|
| Coefficient of variation (CV) | 2.112344071 |
| Kurtosis | 9.778125179 |
| Mean | 0.3815937149 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 2.749117047 |
| Sum | 340 |
| Variance | 0.6497282437 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 678 | |
| 1 | 118 | 13.2% |
| 2 | 80 | 9.0% |
| 5 | 5 | 0.6% |
| 3 | 5 | 0.6% |
| 4 | 4 | 0.4% |
| 6 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 0 | 678 | |
| 1 | 118 | 13.2% |
| 2 | 80 | 9.0% |
| 3 | 5 | 0.6% |
| 4 | 4 | 0.4% |
| 5 | 5 | 0.6% |
| 6 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 6 | 1 | 0.1% |
| 5 | 5 | 0.6% |
| 4 | 4 | 0.4% |
| 3 | 5 | 0.6% |
| 2 | 80 | 9.0% |
| 1 | 118 | 13.2% |
| 0 | 678 |
| Distinct | 681 |
|---|---|
| Distinct (%) | 76.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| 347082 | 7 |
|---|---|
| CA. 2343 | 7 |
| 1601 | 7 |
| 3101295 | 6 |
| CA 2144 | 6 |
| Other values (676) |
Length
| Max length | 18 |
|---|---|
| Median length | 6 |
| Mean length | 6.750841751 |
| Min length | 3 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 547 ? |
|---|---|
| Unique (%) | 61.4% |
Sample
| 1st row | A/5 21171 |
|---|---|
| 2nd row | PC 17599 |
| 3rd row | STON/O2. 3101282 |
| 4th row | 113803 |
| 5th row | 373450 |
Common Values
| Value | Count | Frequency (%) |
| 347082 | 7 | 0.8% |
| CA. 2343 | 7 | 0.8% |
| 1601 | 7 | 0.8% |
| 3101295 | 6 | 0.7% |
| CA 2144 | 6 | 0.7% |
| 347088 | 6 | 0.7% |
| S.O.C. 14879 | 5 | 0.6% |
| 382652 | 5 | 0.6% |
| LINE | 4 | 0.4% |
| PC 17757 | 4 | 0.4% |
| Other values (671) | 834 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| pc | 60 | 5.3% |
| c.a | 27 | 2.4% |
| a/5 | 17 | 1.5% |
| ca | 14 | 1.2% |
| ston/o | 12 | 1.1% |
| 2 | 12 | 1.1% |
| sc/paris | 9 | 0.8% |
| w./c | 9 | 0.8% |
| soton/o.q | 8 | 0.7% |
| 347082 | 7 | 0.6% |
| Other values (709) | 955 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 248 |
|---|---|
| Distinct (%) | 27.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 32.20420797 |
| Minimum | 0 |
|---|---|
| Maximum | 512.3292 |
| Zeros | 15 |
| Zeros (%) | 1.7% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.1 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 7.225 |
| Q1 | 7.9104 |
| median | 14.4542 |
| Q3 | 31 |
| 95-th percentile | 112.07915 |
| Maximum | 512.3292 |
| Range | 512.3292 |
| Interquartile range (IQR) | 23.0896 |
Descriptive statistics
| Standard deviation | 49.6934286 |
|---|---|
| Coefficient of variation (CV) | 1.543072528 |
| Kurtosis | 33.39814088 |
| Mean | 32.20420797 |
| Median Absolute Deviation (MAD) | 6.9042 |
| Skewness | 4.78731652 |
| Sum | 28693.9493 |
| Variance | 2469.436846 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 8.05 | 43 | 4.8% |
| 13 | 42 | 4.7% |
| 7.8958 | 38 | 4.3% |
| 7.75 | 34 | 3.8% |
| 26 | 31 | 3.5% |
| 10.5 | 24 | 2.7% |
| 7.925 | 18 | 2.0% |
| 7.775 | 16 | 1.8% |
| 7.2292 | 15 | 1.7% |
| 0 | 15 | 1.7% |
| Other values (238) | 615 |
| Value | Count | Frequency (%) |
| 0 | 15 | |
| 4.0125 | 1 | 0.1% |
| 5 | 1 | 0.1% |
| 6.2375 | 1 | 0.1% |
| 6.4375 | 1 | 0.1% |
| 6.45 | 1 | 0.1% |
| 6.4958 | 2 | 0.2% |
| 6.75 | 2 | 0.2% |
| 6.8583 | 1 | 0.1% |
| 6.95 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 512.3292 | 3 | |
| 263 | 4 | |
| 262.375 | 2 | |
| 247.5208 | 2 | |
| 227.525 | 4 | |
| 221.7792 | 1 | 0.1% |
| 211.5 | 1 | 0.1% |
| 211.3375 | 3 | |
| 164.8667 | 2 | |
| 153.4625 | 3 |
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.1 KiB |
| S | |
|---|---|
| C | |
| Q |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | S |
|---|---|
| 2nd row | C |
| 3rd row | S |
| 4th row | S |
| 5th row | S |
Common Values
| Value | Count | Frequency (%) |
| S | 646 | |
| C | 168 | 18.9% |
| Q | 77 | 8.6% |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| s | 646 | |
| c | 168 | 18.9% |
| q | 77 | 8.6% |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 14 |
| Missing (%) | 1.6% |
| Memory size | 1.1 KiB |
| 성년 | |
|---|---|
| 미성년 | |
| 노년 | 22 |
Length
| Max length | 3 |
|---|---|
| Median length | 2 |
| Mean length | 2.188141391 |
| Min length | 2 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 성년 |
|---|---|
| 2nd row | 성년 |
| 3rd row | 성년 |
| 4th row | 성년 |
| 5th row | 성년 |
Common Values
| Value | Count | Frequency (%) |
| 성년 | 690 | |
| 미성년 | 165 | 18.5% |
| 노년 | 22 | 2.5% |
| (Missing) | 14 | 1.6% |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| 성년 | 690 | |
| 미성년 | 165 | 18.8% |
| 노년 | 22 | 2.5% |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here. A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.
First rows
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Embarked | Age_cut | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 0 | 3 | Braund, Mr. Owen Harris | male | 22.000000 | 1 | 0 | A/5 21171 | 7.2500 | S | 성년 |
| 1 | 2 | 1 | 1 | Cumings, Mrs. John Bradley (Florence Briggs Thayer) | female | 38.000000 | 1 | 0 | PC 17599 | 71.2833 | C | 성년 |
| 2 | 3 | 1 | 3 | Heikkinen, Miss. Laina | female | 26.000000 | 0 | 0 | STON/O2. 3101282 | 7.9250 | S | 성년 |
| 3 | 4 | 1 | 1 | Futrelle, Mrs. Jacques Heath (Lily May Peel) | female | 35.000000 | 1 | 0 | 113803 | 53.1000 | S | 성년 |
| 4 | 5 | 0 | 3 | Allen, Mr. William Henry | male | 35.000000 | 0 | 0 | 373450 | 8.0500 | S | 성년 |
| 5 | 6 | 0 | 3 | Moran, Mr. James | male | 29.699118 | 0 | 0 | 330877 | 8.4583 | Q | 성년 |
| 6 | 7 | 0 | 1 | McCarthy, Mr. Timothy J | male | 54.000000 | 0 | 0 | 17463 | 51.8625 | S | 성년 |
| 7 | 8 | 0 | 3 | Palsson, Master. Gosta Leonard | male | 2.000000 | 3 | 1 | 349909 | 21.0750 | S | 미성년 |
| 8 | 9 | 1 | 3 | Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) | female | 27.000000 | 0 | 2 | 347742 | 11.1333 | S | 성년 |
| 9 | 10 | 1 | 2 | Nasser, Mrs. Nicholas (Adele Achem) | female | 14.000000 | 1 | 0 | 237736 | 30.0708 | C | 미성년 |
Last rows
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Embarked | Age_cut | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 881 | 882 | 0 | 3 | Markun, Mr. Johann | male | 33.000000 | 0 | 0 | 349257 | 7.8958 | S | 성년 |
| 882 | 883 | 0 | 3 | Dahlberg, Miss. Gerda Ulrika | female | 22.000000 | 0 | 0 | 7552 | 10.5167 | S | 성년 |
| 883 | 884 | 0 | 2 | Banfield, Mr. Frederick James | male | 28.000000 | 0 | 0 | C.A./SOTON 34068 | 10.5000 | S | 성년 |
| 884 | 885 | 0 | 3 | Sutehall, Mr. Henry Jr | male | 25.000000 | 0 | 0 | SOTON/OQ 392076 | 7.0500 | S | 성년 |
| 885 | 886 | 0 | 3 | Rice, Mrs. William (Margaret Norton) | female | 39.000000 | 0 | 5 | 382652 | 29.1250 | Q | 성년 |
| 886 | 887 | 0 | 2 | Montvila, Rev. Juozas | male | 27.000000 | 0 | 0 | 211536 | 13.0000 | S | 성년 |
| 887 | 888 | 1 | 1 | Graham, Miss. Margaret Edith | female | 19.000000 | 0 | 0 | 112053 | 30.0000 | S | 미성년 |
| 888 | 889 | 0 | 3 | Johnston, Miss. Catherine Helen "Carrie" | female | 29.699118 | 1 | 2 | W./C. 6607 | 23.4500 | S | 성년 |
| 889 | 890 | 1 | 1 | Behr, Mr. Karl Howell | male | 26.000000 | 0 | 0 | 111369 | 30.0000 | C | 성년 |
| 890 | 891 | 0 | 3 | Dooley, Mr. Patrick | male | 32.000000 | 0 | 0 | 370376 | 7.7500 | Q | 성년 |